Communication systems utilize either wire or wireless transmission according to adopted standards. Implementations can range from local wireless networks in the home, to the national and international cell phone networks, to the worldwide Internet.
Communication systems typically conform to one or more of a number of existing standards. Wireless standards include the Institute of Electrical and Electronics Engineers (IEEE) 802.11 wireless local area network (WLAN), the advanced mobile phone services (AMPS), Bluetooth, global system for mobile communications (GSM), code division multiple access (CDMA), local multi-point distribution system (LMDS), multi-channel-multi-point distribution systems (MMDS), and various proprietary implementations of such standards.
Wireless devices in a network, such as a laptop computer, personal digital assistant, video projector, or WLAN phone, can communicate either directly or indirectly to other users or devices on the network. In direct communication systems, often referred to as point-to-point communication systems, the two devices are assigned one or more communication radio frequency (RF) channels, and the devices communicate directly over those channels. In indirect communication systems, the devices communicate through an intermediary device, such as an associated base station for cellular services, or an access point for home or office WLAN networking, on an assigned channel. To complete the connection, the access point or base station communicates with the pair directly, using the system controller, the Public switch telephone network (PSTN), the Internet, or some other wide area network.
It is well known that better channel estimation and equalization can enhance wireless link performance, either through extending the link range, or increasing data throughput rates. In noisy channel conditions, performance often suffers because of inaccurate channel estimation, or channel training. A further problem often encountered is instability in the analog radio frequency (RF) circuitry, which is often most pronounced early in the packet, during the channel training portion of the preamble. This introduces an error in the channel estimation that can lead to packet loss, and degraded link stability. These problems are prevalent in multi-input-multi-output (MIMO) orthogonal frequency domain modulation (OFDM) communication systems. This is of particular interest in wireless communications systems conforming to the 802.11(n) standard adopted by IEEE because two modes of operation are employed, one being mixed mode and another being Greenfield.
Methods to improve OFDM channel estimation involve smoothing in the frequency domain (Perahia 2008), or by using a time-domain formulation (Edfors, et al 2004). The improvement through frequency domain smoothing is limited; particularly in multipath conditions in which case smoothing can actually degrade performance. The time domain minimum mean-squared error (MMSE) formulation methods are not desirable because they require additional fast fourier transform (FFT)/inverse fast fourier transform (IFFT) modules, which are complex and costly to implement.
Another known method to improve channel estimation/equalization is to implement an adaptive channel estimation/training algorithm that updates the estimate during the data portion of the packet. Adaptive methods can be complex, and typically take time to converge, during which time an error can occur.
One simple method to solve the 802.11(n) OFDM channel estimation problem is to use the standard designated training fields in order to perform the channel estimation/equalization function. However, this can be sub-optimal, particularly when RF transients corrupt the preamble portion of the packet, or in noisy channel conditions, as much as 2 dB receiver sensitivity can be lost. Alternately, a frequency domain smoother can be used to smooth out noise in the channel estimate by taking advantage of assumed correlation between adjacent subcarriers. However, the smoother can actually degrade performance when this correlation assumption is invalid. Time domain methods are another way to enhance channel estimation accuracy, but require expensive FFT modules for each additional receiver chain. Lastly, adaptive estimation/equalization methods (LMS) can be used to slowly adapt the estimate during the data portion of the packet. However, for short packets, the estimate may not converge fast enough to provide any performance benefit.
Thus, there exists a need to provide a method and apparatus for improving channel estimation and subsequent equalization for receivers of multi-input-multi-output (MIMO) orthogonal frequency domain modulation (OFDM) communication systems that includes a header during transmission of information used to decode and enhance the accuracy of the channel training.